MicroRNAs are small noncoding RNAs that can regulate gene expression, and they can be involved in the regulation of mammary gland development. The differential expression of miRNAs during mammary gland development is expected to provide insight into their roles in regulating the homeostasis of mammary gland tissues. To screen out miRNAs that should have important regulatory function in the development of mammary gland from miRNA expression profiles and to predict their function, in this study, the target genes of differentially expressed miRNAs in the lactating mammary glands of Laoshan dairy goats are predicted, and then the functions of these miRNAs are analyzed via bioinformatics. First, we screen the expression patterns of 25 miRNAs that had shown significant differences during the different lactation stages in the mammary gland. Then, these miRNAs are clustered according to their expression patterns. Computational methods were used to obtain 215 target genes for 22 of these miRNAs. Combining gene ontology annotation, Fisher’s exact test, and KEGG analysis with the target prediction for these miRNAs, the regulatory functions of miRNAs belonging to different clusters are predicted. 1. Introduction MicroRNAs (miRNAs) are endogenous ~22？nt？RNAs that play an important role in regulating gene expression through sequence-specific base pairing with target mRNAs in animals and plants [1]. In animal cells, most studied miRNAs are formed into imperfect hybrids with sequences in the mRNA 3′-untranslated region (3′-UTR) and regulate cell development, cell proliferation, cell death, and morphogenesis [2, 3]. The key to understanding the miRNA regulatory mechanism is the ability to identify their regulatory targets. Computational prediction methods have developed into important approaches for obtaining these regulatory targets [4–6]. In plants, many miRNA targets can be predicted with confidence simply by searching for mRNAs with extensive complementarity to the miRNAs [7]. However in animals, miRNA target prediction is more difficult because of the incomplete complementary of the miRNA with its target, leading to many false predictions [4, 8]. TargetScan predicts biological targets of miRNAs by searching for the presence of conserved 8mer and 7mer sites that match the seed region of each miRNA [9]. PITA can predict miRNA targets in consideration of mRNA secondary structure [10]. miRGen is an integrated database that contains animal miRNA targets according to combinations of six target prediction programs. The mammary gland undergoes cycles of cell division,
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